Showing papers in "Engineering Blasting in 2015"
Journal Article•
TL;DR: The blasting classification of rock mass was established based on weighted clustering analysis as mentioned in this paper, and the production practice showed that the method of clustering analyses of comprehensin weight was suitable for the actual situation.
Abstract: Based on the engineering practice and the results of previous researches,four indexes inchuding the platts firmness coefficient,wave impedance,explosive consumption and average fracture spacing were selected to judge the blasting classification of rock massThe comprehensive weight method of analytic hierarchy process and the variation coefficient method were adopted to avoid the flaws that subjective and objective weight methods used in the determination of weight coefficientThe blasting classification of rock mass was established based on weighted clustering analysisThe production practice showed that the method of clustering analysis of comprehensin weight was suitable for the actual situation
2 citations
Journal Article•
TL;DR: In this paper, the authors extracted the time frequency characteristics of underwater explosion signal of metal detonating cord using wavelet transform time-frequency analysis method, and the results showed that the signal of shock wave could be decomposed by EMD with its self-adaptability.
Abstract: Traditional wavelet transform time-frequency analysis method has some limitations when the signal of underwater explosion is extracted.In order to obtain the time frequency characteristics of underwater explosion signal of metal detonating cord,the time frequency signal data were extracted by HHT.The result showed that the signal of shock wave could be decomposed by EMD with its self-adaptability,and it was suitable to analysis of underwater explosion signal of metal detonating cord.The HHT method could effectively extract time-frequency characteristics of the signal of metal detonating cord underwater,the main frequency of shock wave signal was distributed between 0 to 40 kHz,the largest energy was concentrated in low frequency signal that lower than 20 kHz,and the frequency higher than 80 kHz accounted low proportion.The energy mainly concentrated before 80μs within 3 sections,and the time corresponding to the peak energy of each section were 3μs,5μs and 16μs respectively.
1 citations